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overview_get_live_configs

Fetch live configs; mutation_ref saves same-writer proof (max 50)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
entitiesYes
mutation_refNo
response_modeNocompact
metadata_contract_versionNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
messageNo
retryableNo
support_refNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedOutput schema / $defs
      Added value: +{
      +  "s0": {
      +    "properties": {
      +      "can_report_stored_total": {
      +        "type": "boolean"
      +      },
      +      "reason": {
      +        "type": "string"
      +      },
      +      "zero_proven": {
      +        "type": "boolean"
      +      }
      +    },
      +    "required": [
      +      "can_report_stored_total",
      +      "zero_proven",
      +      "reason"
      +    ],
      +    "type": "object"
      +  }
      +}
    • addedOutput schema / else / properties / read_evidence
      Added value: +{
      +  "description": "Proofs apply independently to returned metrics and scope as stored/observed. A new read_ref is a call identifier, never a source watermark. False or missing proof means unknown, not zero. Fingerprints correlate requests/results in audits; they are not authorization or pagination tokens.",
      +  "properties": {
      +    "artifact_returned": {
      +      "type": "boolean"
      +    },
      +    "configuration": {
      +      "properties": {
      +        "account_inventory_enumerated": {
      +          "const": false
      +        },
      +        "all_campaigns_paused_proven": {
      +          "const": false
      +        },
      +        "requested_ids_complete": {
      +          "type": "boolean"
      +        },
      +        "scope": {
      +          "const": "requested_entity_ids_only"
      +        }
      +      },
      +      "type": "object"
      +    },
      +    "mmp": {
      +      "properties": {
      +        "can_report_scoped_totals": {
      +          "type": "boolean"
      +        },
      +        "provider_cache_max_age_seconds": {
      +          "const": 90
      +        },
      +        "reason": {
      +          "type": "string"
      +        },
      +        "scope": {
      +          "const": "linked_apps_queried_channels_and_windows"
      +        },
      +        "source_observed_at": {
      +          "type": "null"
      +        }
      +      },
      +      "type": "object"
      +    },
      +    "read_ref": {
      +      "pattern": "^read_[0-9a-f]{32}$",
      +      "type": "string"
      +    },
      +    "request_fingerprint": {
      +      "type": "string"
      +    },
      +    "result_fingerprint": {
      +      "type": "string"
      +    },
      +    "scopes": {
      +      "items": {
      +        "properties": {
      +          "all_campaigns_paused_proven": {
      +            "const": false
      +          },
      +          "funnel": {
      +            "additionalProperties": {
      +              "$ref": "#/$defs/s0"
      +            },
      +            "maxProperties": 32,
      +            "type": "object"
      +          },
      +          "index": {
      +            "type": "integer"
      +          },
      +          "inventory_anchor": {
      +            "type": [
      +              "string",
      +              "null"
      +            ]
      +          },
      +          "inventory_coverage": {
      +            "type": "string"
      +          },
      +          "inventory_source_observed_at": {
      +            "type": [
      +              "string",
      +              "null"
      +            ]
      +          },
      +          "metrics": {
      +            "additionalProperties": {
      +              "$ref": "#/$defs/s0"
      +            },
      +            "type": "object"
      +          },
      +          "metrics_source_observed_at": {
      +            "type": [
      +              "string",
      +              "null"
      +            ]
      +          },
      +          "range_complete": {
      +            "type": [
      +              "boolean",
      +              "null"
      +            ]
      +          },
      +          "scope": {
      +            "const": "stored_query"
      +          }
      +        },
      +        "type": "object"
      +      },
      +      "maxItems": 10,
      +      "type": "array"
      +    }
      +  },
      +  "required": [
      +    "read_ref",
      +    "request_fingerprint",
      +    "result_fingerprint"
      +  ],
      +  "type": "object"
      +}
  2. First observed

TDQS

C2.6/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations are provided (readOnlyHint=false, destructiveHint=false, openWorldHint=false), so the safety bar is lower. The description does add real behavioral context beyond them: passing mutation_ref causes state to be saved as 'same-writer proof', which explains the non-read-only annotation. However it discloses nothing about permissions, freshness/caching of 'live' data, or the compact vs standard response behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

It is a single front-loaded sentence with no filler, which is good. But it is telegraphic to the point of opacity — the semicolon-joined clauses compress two concepts (fetch behavior, mutation_ref side effect) into a string that is hard to parse without the schema open.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists so return values need not be described, but for a 4-parameter tool with zero schema description coverage, nested entity objects, and a state-saving side effect, the description leaves too much unspecified. It gives no picture of the request/response shape or the read-vs-update workflow with its siblings.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% and there are 4 parameters, so the description must carry the burden. It only glosses mutation_ref ('saves same-writer proof') and restates the entities cap of 50 that the schema already enforces via maxItems; response_mode and metadata_contract_version are entirely unexplained, and the entities object structure is undocumented in prose.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The verb 'Fetch' is clear and the object 'live configs' maps to the overview family, but it never says which entities' configs (campaign/adset/ad, implied only by the nested schema) or what a 'live config' contains. An agent can guess it is the read counterpart to the overview_update_* siblings, but the description does not differentiate itself from them explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no explicit when-to-use statement and no mention of alternatives among the many overview_update_* / overview_update_confirm siblings. The only contextual hint is the parenthetical about mutation_ref, which implies a 'read after your own write' flow but is phrased as a mechanism, not as guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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